• 제목/요약/키워드: Dynamics identification

검색결과 309건 처리시간 0.028초

빠른 신경망을 이용한 실시간 현가시스템 인식 (Suspension System Identification using Fast Neural Networks)

  • 송광현;설남오;이창구;김성중
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 B
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    • pp.561-563
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    • 1997
  • In this paper, we identified the Black-box system with serious nonlinerity and fast dynamics using Neural Network. This NN have new structure and learned by RLS. It identify system in real-time without priori data. We use this NN to 7-DOF vehicle identification.

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자세의 유지성 및 안정성에 관한 해석 (Identification of postural steadiness and stability: state-of-the-art)

  • 정병용;박경수
    • 대한인간공학회지
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    • 제15권1호
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    • pp.53-67
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    • 1996
  • Since Romberg's test in 1953, the analysis of postural sway during upright stance has been widely used as a tool for evaluating balance and disorders of the postural control system. This review describes the methods that have been used to evaluste the static and dynamic performance of the postural control system. Various identification methods of postural control system based on standing balance are discussed and measures of postural sway are described. The application areas of standign balance research, with an emphasis on postural control evaluations, are also briefly described. This review can be used to gain an understanding of the dynamics of human standing balance.

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Neural Model Predictive Control for Nonlinear Chemical Processes

  • Song, Jeong-Jun;Park, Sunwon
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.899-902
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    • 1993
  • A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

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Using Keystroke Dynamics for Implicit Authentication on Smartphone

  • Do, Son;Hoang, Thang;Luong, Chuyen;Choi, Seungchan;Lee, Dokyeong;Bang, Kihyun;Choi, Deokjai
    • 한국멀티미디어학회논문지
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    • 제17권8호
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    • pp.968-976
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    • 2014
  • Authentication methods on smartphone are demanded to be implicit to users with minimum users' interaction. Existing authentication methods (e.g. PINs, passwords, visual patterns, etc.) are not effectively considering remembrance and privacy issues. Behavioral biometrics such as keystroke dynamics and gait biometrics can be acquired easily and implicitly by using integrated sensors on smartphone. We propose a biometric model involving keystroke dynamics for implicit authentication on smartphone. We first design a feature extraction method for keystroke dynamics. And then, we build a fusion model of keystroke dynamics and gait to improve the authentication performance of single behavioral biometric on smartphone. We operate the fusion at both feature extraction level and matching score level. Experiment using linear Support Vector Machines (SVM) classifier reveals that the best results are achieved with score fusion: a recognition rate approximately 97.86% under identification mode and an error rate approximately 1.11% under authentication mode.

방향 시계열에 의한 회전체 동특성 규명: (I) 모델링 및 해석 (Directional ARMAX Model-Based Approach for Rotordynamics Identification, Part 1 : Modeling and Analysis)

  • 박종포;이종원
    • 소음진동
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    • 제8권6호
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    • pp.1103-1112
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    • 1998
  • A new time series method, directional ARMAX (dARMAX) model-based approach. is proposed for rotor dynamics identification. The dARMAX processes complex-valued signals, utilizing the complex modal testing theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible, to account for the dynamic characteristics inherent in rotating machinery. This paper is divided into two parts : The dARMAX modeling, analysis. and fitting strategy are presented in the first part. whereas a evaluation of its performance characteristics based on both simulated and experimental data is presented in the second.

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초저전력 마이크로 서보시스템의 모델식별을 위한 계측 파라미터 선정 기법 (Sensing Parameter Selection Strategy for Ultra-low-power Micro-servosystem Identification)

  • 한봉수
    • 제어로봇시스템학회논문지
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    • 제20권8호
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    • pp.849-853
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    • 2014
  • In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

PCR-DGGE 방법을 이용한 북한강 수계 호수의 플랑크톤 군집 분석 (Plankton community analysis in the lake of North-Han river system using PCR-DGGE method)

  • 김윤정;김민경;이상돈
    • 한국습지학회지
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    • 제14권3호
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    • pp.419-428
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    • 2012
  • 식물플랑크톤의 동정은 숙련된 전문가에게도 어려운 과제이다. 별 특징없는 외형과 다양한 크기와 종은 형태학적으로 구분하기에 어려움이 있다. 본 연구에서는 미생물 군집의 다양성을 분석하는데 효과적인 fingerprinting 기법인 PCR-DGGE 방법을 사용하여 이런 형태학적 동정의 제한점을 보완하고자 하는데 목적이 있다. 5곳의 호수 샘플로부터 2008년 8월 총 46개의 band를 찾을 수 있었고, 2008년 11월 총 26개 band를 찾을 수 있었다. 이 fingerprint 결과는 각각 다른 샘플링 장소를 비교하는데 용이하였다. 본 연구에서 PCR-DGGE 방법은 북한강 호수들의 플랑크톤 군집의 다양성을 파악하는데 사용되었고, 이 DGGE 기법이 플랑크톤의 동정기법으로써의 가능성을 검토해보았다.

Crack identification with parametric optimization of entropy & wavelet transformation

  • Wimarshana, Buddhi;Wu, Nan;Wu, Christine
    • Structural Monitoring and Maintenance
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    • 제4권1호
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    • pp.33-52
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    • 2017
  • A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.

Moving force identification from bending moment responses of bridge

  • Yu, Ling;Chan, Tommy H.T.
    • Structural Engineering and Mechanics
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    • 제14권2호
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    • pp.151-170
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    • 2002
  • Moving force identification is a very important inverse problem in structural dynamics. Most of the identification methods are eventually converted to a linear algebraic equation set. Different ways to solve the equation set may lead to solutions with completely different levels of accuracy. Based on the measured bending moment responses of the bridge made in laboratory, this paper presented the time domain method (TDM) and frequency-time domain method (FTDM) for identifying the two moving wheel loads of a vehicle moving across a bridge. Directly calculating pseudo-inverse (PI) matrix and using the singular value decomposition (SVD) technique are adopted as means for solving the over-determined system equation in the TDM and FTDM. The effects of bridge and vehicle parameters on the TDM and FTDM are also investigated. Assessment results show that the SVD technique can effectively improve identification accuracy when using the TDM and FTDM, particularly in the case of the FTDM. This improved accuracy makes the TDM and FTDM more feasible and acceptable as methods for moving force identification.

Strategic Analysis Evolution: Scenario Planning and Simulation Based on The Methodology of System Dynamics

  • Bassi, Andrea M
    • 한국시스템다이내믹스연구
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    • 제5권2호
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    • pp.199-216
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    • 2004
  • The present study is aimed at developing the optimal instruments for dispelling the uncertainty factors during the formulation of strategies for corporate development. The objective is the creation of a complete model of strategic analysis, which encompasses both the environment (internal and external) and the management rational component. This model -built on the analysis of three corporate cases - is concretized by a simulation for testing the strategy by the means of software which enables the users to cope with a dynamic and complex corporate environment. The research questions regard the development of a complete strategic analysis, which covers the entire decision-making process; the concrete assessment of the business strategy on the basis of quantitative data: the identification and enhancement of the critical variables of business administration, in such a complex and dynamic reality as the corporate environment.

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